Join our Good Problems Team to identify pressing global problems and design impactful funding programmes to solve them. 🌏
Our Good Problems Team at Science Practice works with science and innovation funders to identify pressing global challenges and design programmes to act on them. We have designed over 40 innovation programmes including the £10M Longitude Prize and our clients include Wellcome, the Humanitarian Innovation Fund and Nesta.
We are a dedicated team of four with skills ranging from design and research to social entrepreneurship, programming and radio. Our ambition is to maximise the impact of existing resources by helping funders make informed and transparent strategic decisions.
We work across a diverse range of domains, from mental health and urban transport to nutrition and gender-based violence (GBV). Right now, we’re scoping opportunities for public engagement in biomedical and health science and designing a series of innovation challenges for the humanitarian water, sanitation, and hygiene (WASH) sector.
We are looking for someone with diverse research experience to support us with the development and design of innovation funding programmes in the humanitarian space. Recent similar projects include the development of the Menstrual Hygiene Management Challenge and the WASH Evidence Challenge for the Humanitarian Innovation Fund.
We are open to interviewing both early-career and experienced researchers with a diverse range of research experience including, but not limited to, exploratory research, action research, policy-oriented research or human-centred research.
We are looking for someone available to start in January 2020.
The role will involve:
In order to apply for this job, you should have the right to work in the UK.
We value diversity at our company. This is core to our work as developing a robust understanding of problems requires a diversity of thought, experience and perspectives. We welcome applications from people of all backgrounds and ages.
To apply, please submit your details via this form.
The deadline for applications is 9am on Monday, 13th January 2020.
We will be in touch to arrange a convenient time for an interview by Wednesday, 15th January 2020.
We will start interviewing eligible applicants the w/c 13 January 2020.
We look forward to hearing from you! 🙌
No agencies, please.
This year, our Good Problems team explored running workshops with funders as a way of sharing our tools for identifying and prioritising problems. This gave us an opportunity to understand how funders are thinking about their role and impact, and how we can evolve the support we offer.
This post features two workshops that we think reflect the sector’s shifting orientation toward problem-led approaches: a workshop with a group of Finnish foundations on how to collaborate around problems, and another with the Centre for Ageing Better on prioritising problems.
We often work with funders who want to know who else is working on the problems they are interested in. It helps them understand where they fit in and prevents duplication of work. But some funders are taking steps to actively collaborate with other funders around particular problems. This helps them have more impact than they could have by acting independently.
Jouni Lounasmaa, Executive Director of the KAUTE Foundation, was interested in a more collaborative approach. He wanted to hold a workshop where Finnish foundations could meet, share best practices, and explore how they could work together to tackle climate change and other pressing problems. Working with Jouni, we co-designed activities to help them share and understand the problems they were interested in, and see how they could work together to solve them.
The workshop gathered a dozen foundations, each with its own distinct history, approach to grant-making, and set of priorities. To start with, we invited them to get to know each other’s interests by forming groups and sharing problems they were currently working on or would like to work on. We then asked them to cluster the problems, select a cluster they were particularly interested in, and prototype a shared programme to address that problem.
To help them scope out the potential programmes, we asked funders to fill out a Rapid research and validation plan. They wrote down what they knew about the problem, what they didn’t know, and what they could do to fill the gaps in their knowledge. We often use a version of this validation plan in our own research on problems because it works well to highlight what we still need to learn and to plan how we’ll do this, doubling as a to-do list we can revisit periodically as our understanding of a problem evolves.
Taking this problem-focussed approach made it easier for individual funders to understand what they could work on and how their resources and expertise might be complementary. When you lead with problems, conversations about potential collaborations become much more concrete and grounded.
Science Practice provided a pragmatic approach to an often philosophically slanted discussion. The workshop has inspired us to embark on a journey towards well-researched and problem-oriented co-funding. I have found the tools to be very useful in my own work.
Foundations don’t often have the opportunity to meet and explore how to work together on solving problems. However, creating space for these activities is becoming increasingly relevant given the urgency and complexity of the problems we are facing. These problems require a shared vision, action plan, and complementary programmes that build on each other to maximise impact. We were excited by this open and collaborative gathering in Finland and are looking to create similar opportunities for funders in the UK to come together and explore how to tackle important systemic issues.
Even when funders have decided on a problem area, it can be challenging to define specific opportunities to intervene. Having a clear set of criteria for problems can support more open and constructive conversations and facilitate decision-making. It can also help funders clearly articulate strengths and pinpoint the biggest opportunities for impact.
The Centre for Ageing Better’s goal is to create a society where everyone enjoys a good later life. One challenge they face is setting priorities among the diverse range of problems they could tackle. For example, should they focus on workers over 50 with health conditions struggling to get back into work – or on transforming UK workplaces into healthy places to increase disability-free life expectancy?
To inform their decision-making, we designed and ran a workshop with around 20 team members focused on developing internal criteria for identifying and defining suitable problems for Ageing Better and exploring how the team could use these criteria to focus their work.
Before the workshop, we shared a short survey with the Ageing Better team to learn more about how they make prioritisation decisions, who is involved, and what criteria they use (whether these are explicit or not). We used the responses as a starting point for the workshop content and activities. This was important because it meant that the workshop built on the team’s own ideas and allowed them to advance and challenge their thinking rather than start from a blank slate.
For the main activity, we created a long-list of the criteria mentioned in the surveys and asked the participants, in groups, to discuss and refine these before selecting the five they thought were most relevant for Ageing Better team members to consider when deciding on which problems to pursue.
We then asked groups to use their resulting criteria to prioritise between three problems they were currently struggling to choose between. The activity proved challenging but productive. The teams said that making decisions over which problem to pursue over others was difficult because the criteria didn’t feel right just yet – the criteria were either trying to cover too many things at once, weren’t as relevant in practice as they had seemed when proposed, or were missing completely. This exercise proved useful for quickly testing the emerging criteria and understanding how they could be used in practice.
By the end of the session, the teams were already thinking of the next iteration of the criteria and how they could use different subsets at different stages of the research and prioritisation.
Having a defined set of criteria for this type of work can facilitate more open conversations and highlight hidden assumptions or potential misunderstandings around an organisation’s role and priorities. Being able to clarify these and speak openly and confidently about them means that you can be more strategic about the problems you decide to prioritise and the impact you can achieve.
With each conversation and workshop that we have with funders, we see a change in the narrative. Funders are increasingly reflecting on their own activities and looking for more strategic and collaborative ways to increase their impact. While the intent exists, there is still a lot of work to be done to understand how to best achieve this, what works, and what doesn’t. However, this learning needs to happen at an accelerated pace as the global problems facing us are only growing in scale and complexity.
Within this space, we see our role as helping funders become more strategic about the problems they prioritise to achieve greater impact, sharing best practice from across the sector, and defining common goals to enable collaborations. If you’re interested in what a problem-led approach could do for your funding organisation, we’d love to help.
For a while we’ve been interested in collective intelligence and how it can be used to identify and tackle important problems. In a previous post, we looked at methods that could help democratise futures thinking, many of which have a collective intelligence aspect. To explore more, I went to Nesta’s conference 21st century common sense: Using collective intelligence to tackle complex social challenges. It gave a good overview of current activity and thinking on the topic, and I wanted to share some of the themes I came across there.
According to Nesta’s new collective intelligence playbook.
Collective intelligence is created when people work together, often with the help of technology, to mobilise a wider range of information, ideas and insights to address a social challenge.
This is not something new – parliaments, business meetings, and scientific institutions all enable collective intelligence. But new technologies offer new options – Wikipedia helps people collaborate to build an encyclopedia, Loomio helps people make decisions without meetings, and the Human Diagnosis Project brings together medical professionals to collaborate on diagnosis.
Group decision making is central to collective intelligence. I got to experience the challenges of this first-hand through an immersive theatre experience called The Justice Syndicate.
I was one of a 12-member jury asked to decide whether a fictional top surgeon accused of a serious crime was guilty or not. Guided by instructions on tablet computers we read forensics documents, saw videoed witness testimony, and read out lawyers’ statements. Periodically we had discussions, and voted on whether we thought he was guilty. It was an intense experience - the subject matter was disturbing, and the realism of the situation gave me a sense of responsibility for making the right decision.
After we’d made our decision, neuroscientist Kris De Meyer shared what he’d found through his work on the project. As well as telling us about the science, he said that it was unusual for us to have converged so rapidly on a unanimous verdict. Often more than one final vote is needed to get to unanimity, and sometimes there is a lengthy and heated discussion between two opposing groups.
The experience of going through this process and hearing the variety of ways different juries made decisions lead me to question my own rationality. Although we can know intellectually about the biases we all have, experiencing it makes it more real. It would be great to see these immersive decision making experiences used more widely, so people can experience the ways in which their thinking can go wrong.
Questions we’d like to explore more
Several speakers thought it was important to draw on new sources of data such as social media, which can be more useful than survey data. For example, Maesy Angelina from Pulse Lab Jakarta described their project Haze Gazer, which identifies pollution from forest fires in Indonesia using both satellite imagery and data from social media.
Filling gaps in existing data is also important, especially if these gaps harm particular groups in society. For example, Jessica Sena the OpenStreetMap group GeoChicas mentioned that only 3% of OpenStreetMap contributors are women, which affects the information that gets added to their maps.
Maesy Angelina from Pulse Lab Jakarta also emphasised the importance of having “thick data” as well as “big data”. As Tricia Wang defines it
Thick Data is data brought to light using qualitative, ethnographic research methods that uncover people’s emotions, stories, and models of their world.
Combining thick data and big data is a good example of combining the strengths of machines and humans. Pulse Lab Jakarta did this effectively when they used ethnography to understand why they were seeing complaints on social media about school opening times in areas affected by forest fires. By sending ethnographers to the affected areas, they found that children ended up walking a long way through polluted air to get to school, only to find that the school was closed because of the haze.
Questions we’d like to explore more
Several speakers were working on software to help groups make better decisions. For example, Vito Trianni has developed software to give feedback to groups who are making decisions. He hopes that the software can help overcome some of the challenges of group decision making such as herding and overconfidence. Another speaker, David Baltaxe from Unanimous AI presented software inspired by the dynamics of flocks and swarms of animals. It has has been used in forecasting, business decision making, and in helping groups with different political views to set priorities.
Questions we’d like to explore more
When designing problem-led funding programmes we have to draw on the knowledge and wisdom of many people. We read many documents, look at data, talk to experts, and help our clients’ teams make tough prioritisation decisions. We’d like to explore how we could use collective intelligence to help with this.
As well as informing our own work, we think collective intelligence is a useful way of thinking about how society as a whole can understand, prioritise, and solve problems. We look forward to seeing how the field evolves and what innovative projects emerge from funding programmes like the recent collective intelligence grants from Nesta, the Wellcome Trust, the Cloudera Foundation, and Omidyar Network.
If you compare climate change and nuclear war, a lack of humanitarian innovation and a slowdown in scientific discovery, or technology in education and in transport, you might think that these problems are very different from one another. But take a step back and identify what's causing them, and you’ll find they follow similar patterns. We call these patterns problem archetypes.1 Identifying these archetypes can help us identify types of solutions that work across many similar problems.
We’ve been keeping track of problem archetypes as we notice them, and we’re sharing them here as a starting point for developing a more comprehensive list.
So far, we’ve identified eight different problem archetypes. These include:
If we don’t know a problem exists, we can’t make deliberate progress on solving it. Sometimes discovering the problem leads quickly to action, as when the 1985 discovery of the hole in the ozone layer led to the 1987 Montreal Protocol limiting ozone-depleting substances.
But sometimes this process isn’t so simple. Although smoking was suggested as a major cause of lung cancer in the early 20th century, it took multiple lines of evidence developed over the following decades to prove it in the 1940s and 50s. It took several decades more to convince doctors, politicians, and the public of the problem, in large part because of campaigns by the tobacco industry.
Sometimes people don’t see something as a problem because of their values. Differences in values are key reasons for disagreement over whether factory farming, economic inequality, and abortion are important problems.
Values also affect people’s approaches to solving problems. For example, anticapitalist climate campaigners often disagree with proposals such as carbon taxes, arguing for a more radical reconfiguration of the economy.
In the early stages of solving a problem, there may be a lack of ideas of what to do to get started. The burgeoning field of AI policy is going through this right now: actors in this field are working to identify the different facets of the problem, and propose initial solutions, but there isn't yet consensus over where efforts should be focused.
Later on, there may be plenty of solutions, but inadequate evidence as to what will work best. A lack of good evidence is one of the most common issues we come across. For example, Steve Higgins, Professor of Education at Durham University, says “Most things in education, we have no idea whether they work.” This issue even affects areas with relatively good evidence, such as medicine. For example, many evidence-based medical guidelines have limited applicability when patients have more than one condition.
Some problems lack sufficient funding. For example, an IPCC report suggests that to limit global warming to 1.5°C we need a $2.4 trillion investment in the energy system every year between 2016 and 2035, which is about 2.5% of global GDP.2 But 2016 saw a global $455 billion spend on addressing climate change overall, which is only 19% of the IPCC recommended investment.
Often there is insufficient funding because a problem affects people who can’t pay for solutions. For example, because snakebite mainly affects poor people in the developing world, there isn’t a big enough financial incentive to make antivenom for them. Similarly, the future people affected by climate change are unable to pay us to prevent it. If they could, there would be much more motivation for people to solve the problem now.
Funding amount is not the only problem - how it is allocated also matters. For example, the humanitarian sector is hampered by funders who are risk-averse, inflexible, and give short-term grants. There is a similar situation in science funding, which constrains research.
The nonprofit sector, in general, suffers from problems with the structure of funding. Donors often prefer charities with low administrative (aka overhead) costs. But this can make it difficult for charities to operate effectively. Another difficulty for charities arises when donors restrict their funding to a particular programme, rather than giving the charity a grant that can be used on any part of their work. This can fragment charities’ strategies.3
Money is not the only resource constraint. Skill is another major one. For example, the humanitarian sector struggles with scaling innovations partly because there is a lack of skill on scale in the sector. In EdTech, teachers and school leaders often lack the expertise to properly evaluate EdTech. In the low-income countries, there is a shortage of many skilled professionals such as psychiatrists.
Even if there are incentives to solve a problem, they can be misaligned. This often happens in situations where it is difficult to measure and incentivise what we want, but decisions are made based on these flawed metrics anyway.4 For example, judging teachers based on student’s exam results does fit with the goal of education, but too much emphasis on this metric can lead to teaching to the test.
Fields that form to tackle a problem often benefit from the involvement of organisations that provide the field with infrastructural services. Rather than working directly on the problem, these organisations help by coordinating work, developing and sharing evidence, and building networks.5 For example, in global health, there is the Disease Control Priorities Project, which reviews the evidence on interventions to address disease in low-resource settings.
The development of a new type of infrastructural organisation can have a big impact on a field. For example, startup accelerators have become a major part of the tech startup ecosystem, beginning with Y Combinator in 2005. In charity funding, the charity evaluator GiveWell has had a big impact – it estimates that it influences ~$150 million per year in donations.
Sometimes, people want to take action on a problem, but doing so would put them at a disadvantage compared to others. Without a way to trust each other, it’s difficult for any of the parties to take action. For example, this occurs in climate change, where “other industrialized nations such as the USA (as well as Australia and Canada) have balked at taking action for fear of ‘free riding’ on the part of major developing nations who have become trade competitors.”6
Once we build up our understanding of each problem archetype, we plan to draw on fields like systems science, the economics of market failure, and the study of coordination and cooperation to think about corresponding types of solutions that funders and other actors can develop to address these.
But for now, know of any problem archetypes we’ve missed? Drop us a line at firstname.lastname@example.org
This is a similar idea to Daniel Kim’s System Archetypes. While his approach is focussed on any kind of problem, ours is focussed specifically on large-scale problems that altruistically-motivated people might want to solve. His approach is also rooted more in systems science, whereas we draw on our own experience. We plan to investigate the systems approach more and may incorporate it into our problem archetypes analysis. ↩
“Global model pathways limiting global warming to 1.5°C are projected to involve the annual average investment needs in the energy system of around 2.4 trillion USD 2010 between 2016 and 2035, representing about 2.5% of the world GDP” p. 24 of the IPCC report Global Warming of 1.5°C ↩
Similar to the idea of field-building intermediaries outlined in the article When Building a Field Requires Building a New Organization ↩
Identifying the right problem to solve is an important part of having an impact, but it’s a hard task. Lists of clearly-described problems offer a starting point for finding the right one. They can also help organisations and individuals coordinate around a set of common priorities, as has happened with the UN Sustainable Development Goals
This is why we’ve been working on what we call problem briefs. These are short documents where we describe a problem, evaluate how important it is, and suggest what a philanthropic funder could do to help solve it. We’d like to develop these into a resource where people can explore problems and see how they could contribute towards solving them. We’ve looked for other organisations doing similar work, and wanted to share what we found:
Developing these kinds of resources is part of a wider project that many organisations are independently working on: finding, understanding, and prioritising problems to work on. We’d like to see more of a unified field develop around this kind of work. A first step towards this would be for organisations to share their work so others can build on it. For example, we’d encourage foundations to publish their analyses of problems, which they often keep as internal documents.
In the longer run, we like Bret Victor’s vision of tools for problem-finding. When thinking about how an engineer might find climate change problems to work on, he suggests that she needs “a tool that lets her skim across entire fields, browsing problems and discovering where she could be most useful.” This is not just something that engineers need - anyone wanting to have a large positive impact would benefit from a tool like this.
We are a close team of designers and researchers who are passionate about tackling ambitious and important problems. If you’re looking to grow your impact, we’d love to hear from you!